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Vol. 10, Special Issue, February 2011, pp.71-83



In the Field Application of a New Sensor for Monitoring Road and Runway Surfaces



Dipartimento di Elettronica of Politecnico di Torino,
Corso Duca degli Abruzzi 24, Torino, 10129, Italy

Tel.: +39 011 5644085, fax: +39 011 5644099

E-mail: amedeo.troiano@polito.it, eros.pasero@polito.it, luca.mesin@polito.it



Received: 29 October 2010   /Accepted: 11 January 2011   /Published: 8 February 2011


Abstract: Water and ice detection over road and runway surfaces is important to improve traffic safety and to reduce maintenance costs. An innovative low cost capacitive sensor was developed to estimate the dry, wet, or icy state of surfaces. The reliability and repeatability of the indications of the sensor were investigated in a previous work based on simulations and experiments in laboratory, together with a preliminary short test in the field. This work is devoted to the study of the indications of 4 sensors (standard or bituminized) during continuous data acquisition in the field (at the Turin Airport) lasted 8 months. The indications of different sensors were highly correlated. As one important problem when measuring in the field is due to dirt and salt spread over the road, a preliminary study on the effect of different salt concentrations in the water covering the surface of the sensor was performed. Both simulations and laboratory tests showed that the sensor is not affected by the presence of salt in the water. Considering data measured in the field, the estimated condition of the road provided by the sensors was found to be consistent with the METAR (METeorological Aerodrome Report) message of the Turin Airport, for the whole period of investigation. Correlation was found between data from the sensors and rain, fog, and snowfall. The beginning formation of ice identified by the sensor was found to be in some agreement with the indication of a mathematical model of ice prediction from meteorological data. The possibility of using the indications of the sensor together with weather data to train an algorithm providing a more precise prediction of ice formation is discussed.


Keywords: Ice detection, Road information system, Road pavement condition


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